Eradication of Extreme Poverty Now Has a Number: $318 billion per year
It is believed that a 'modest' 0.3% of global GDP can lift billions out of extreme poverty
Poverty researchers suggest that the world could reduce extreme poverty to near zero with annual spending of roughly $318 billion — equivalent to just 0.3% of global GDP — by using precisely targeted cash transfers.
The estimate comes from a December 2025 National Bureau of Economic Research working paper by Roshni Sahoo of Stanford University, Joshua Blumenstock of UC Berkeley, Paul Niehaus of UC San Diego, Leo Selker of UC Berkeley, and Stefan Wager of Stanford.
Researchers analyzed nationally representative household consumption surveys from 23 countries that account for about half the world’s poor. They framed the problem as one of statistical learning under real-world information constraints and applied data-driven methods — including machine-learning techniques — to optimize targeting of direct income transfers. In those countries, the annual cost to bring the poverty rate down to 1% (from a baseline around 12%) came to approximately $170 billion. Extrapolated globally, the figure reaches $318 billion per year to achieve a similar outcome worldwide.
This is not a universal basic income.
The approach focuses transfers only where needed to close the gap to the World Bank’s $2.15-a-day extreme poverty line, making it far cheaper than a blanket UBI at the same threshold (estimated at $895 billion annually in the study).
The outlay exceeds recent levels of official development assistance (around 0.21% of global GDP) but represents a small fraction of what the world already spends on alcohol (2.2% of GDP) or cosmetics (0.6%).
The headline number assumes highly efficient targeting and delivery — conditions that are imperfect in practice due to identification challenges, leakage risks, and varying national capacities. Yet the current wave of technological change makes large-scale, precise redistribution more feasible than at any prior point. Advances in AI enable better poverty mapping through satellite imagery, mobile data, and predictive models. Digital payment systems could reduce delivery costs and improve traceability. Biometric IDs and fintech platforms further reduce fraud while scaling reach. Paired with the productivity surges expected from AI and automation, these technologies can both lower implementation costs and generate the broader growth that makes poverty eradication self-reinforcing rather than a perpetual fiscal burden.
The binding constraints are now less about raw affordability and more about political will and coordinated international effort to deploy these capabilities at scale.
In an era of rapid tech-driven economic transformation, the $318 billion annual price tag looks less like an insurmountable obstacle and more like a high-leverage investment in human potential.